Article(id=1153986586233525117, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1153986579971429187, articleNumber=null, orderNo=null, doi=10.19812/j.cnki.jfsq11-5956/ts.20241029003, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1730131200000, receivedDateStr=2024-10-29, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1753061442192, onlineDateStr=2025-07-21, pubDate=1740412800000, pubDateStr=2025-02-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1753061442192, onlineIssueDateStr=2025-07-21, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1753061442192, creator=13701087609, updateTime=1753061442192, updator=13701087609, issue=Issue{id=1153986579971429187, tenantId=1146029695717560320, journalId=1149652044408987649, year='2025', volume='16', issue='4', pageStart='1', pageEnd='320', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1753061440699, creator=13701087609, updateTime=1758783495950, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1177986619249406427, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1153986579971429187, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1177986619249406428, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1153986579971429187, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=185, endPage=193, ext={EN=ArticleExt(id=1153986586887836554, articleId=1153986586233525117, tenantId=1146029695717560320, journalId=1149652044408987649, language=EN, title=Determination and principal component analysis on 19 kinds of metal elements in Nelumbo nucifere Gaertn. from different origins by inductively coupled plasma-mass spectrometry, columnId=1153986581653349021, journalTitle=Journal of Food Safety & Quality, columnName=Special Topic: Application of Modern Analysis Instrument in Food Detection, runingTitle=null, highlight=null, articleAbstract=

Objective To establish a method for the analysis of 19 kinds of metal elements in Nelumbo nucifere Gaertn. by inductively coupled plasma-mass spectrometry (ICP-MS), and to compare and analyze the metal elements content from different areas. Methods The Nelumbo nucifere Gaertn. sample was digested by microwave, and the metal elements content was determined by ICP-MS. The metal element fingerprint was drawn, and principal component analysis was performed on the metal element content using SPSS 26.0 software. Results The fingerprint of 19 kinds of metal elements in the Nelumbo nucifere Gaertn. had certain characteristics, and the content of harmful metal elements should be of concerned. Principal component analysis identified 8 main factors and identified B, S, Ca, Mn, Fe, Zn, Sr, Sb, Ba, As, and Pb as characteristic metal elements for Nelumbo nucifere Gaertn.. The correlation of 19 kinds of metal elements with the comprehensive score value of principal component analysis that were positively correlated in decreasing order were as follows: Pb, As, Ba, Zn, Sb, Mg, Cd, K, S, B, Na, Hg, Cu, Fe, Ni, and negatively correlated correlated in decreasing order were as follows: Sr, Mn, Ca, Mo. Conclusion The method is rapid, accurate and sensitive, and can be used for the simultaneous determination of the content of various metal elements in Nelumbo nucifere Gaertn.. It provides the basis for the quality control and safety evaluation of Nelumbo nucifere Gaertn..

, correspAuthors=Qiu-Ling CHEN, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Zhi-Jian LAI, Qiu-Ling CHEN, Guo-Wei LIU, Jin-Jin ZHANG, Yong HUANG, Cheng SHI, Xiao-Bin YANG, Yi-Xin YAO), CN=ArticleExt(id=1153986608954069261, articleId=1153986586233525117, tenantId=1146029695717560320, journalId=1149652044408987649, language=CN, title=电感耦合等离子体质谱法测定不同产地莲子心中19种金属元素及其主成分分析, columnId=1153986581842092705, journalTitle=食品安全质量检测学报, columnName=本期专题:现代分析仪器在食品检测中的应用, runingTitle=null, highlight=null, articleAbstract=

目的 建立莲子心19种金属元素的电感耦合等离子体质谱法(inductively coupled plasma-mass spectrometry, ICP-MS)的分析方法, 并对不同产地莲子心金属元素含量进行比较分析。方法 莲子心样品经微波消解, 采用ICP-MS测定金属元素含量, 并绘制金属元素指纹图谱, 采用SPSS 26.0对金属元素含量进行主成分分析。结果 莲子心19种金属元素指纹图谱具有一定的特征性; 有害金属元素含量应引起关注。主成分分析筛选出8个主因子, 得出B、S、Ca、Mn、Fe、Zn、Sr、Sb、Ba、As、Pb是莲子心的特征金属元素; 与主成分分析结果呈正相关的元素相关性从大到小依次为Pb、As、Ba、Zn、Sb、Mg、Cd、K、S、B、Na、Hg、Cu、Fe、Ni; 呈负相关的元素相关性从大到小依次为Sr、Mn、Ca、Mo。结论 该方法快速、准确、灵敏度高, 适用于测定莲子心多种金属元素含量的同时测定, 为莲子心的质量控制及安全性评价提供依据。

, correspAuthors=陈秋玲, authorNote=null, correspAuthorsNote=
* 陈秋玲(1989—), 女, 硕士, 执业中药师, 主要研究方向为食品药品质量标准研究。E-mail:
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#赖志坚和陈秋玲为共同第一作者

赖志坚(1969—), 男, 硕士, 高级工程师, 主要研究方向为中药质量标准研究。E-mail:

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赖志坚(1969—), 男, 硕士, 高级工程师, 主要研究方向为中药质量标准研究。E-mail:

"}, bioImg=null, bioContent=

赖志坚(1969—), 男, 硕士, 高级工程师, 主要研究方向为中药质量标准研究。E-mail:

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Journal of Anhui Agricultural University, 2020, 47(4): 1-7., articleTitle=Simultaneous determination of 18 metal elements in olive oil by microwave digestion-inductively coupled plasma-mass spectrometry, refAbstract=null)], funds=[Fund(id=1178002189457965759, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986586233525117, awardId=ZYBZH-Y-GD-13, language=CN, fundingSource=国家中药标准化项目(ZYBZH-Y-GD-13), fundOrder=null, country=null), Fund(id=1178002189550240448, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986586233525117, awardId=KMYY20220801, language=CN, fundingSource=中药配方颗粒产品研发项目(KMYY20220801), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1178002185066529398, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986586233525117, xref=null, ext=[AuthorCompanyExt(id=1178002185074918007, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986586233525117, companyId=1178002185066529398, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Kangmei Pharmaceutical Co., Ltd., Shenzhen 518000, China), AuthorCompanyExt(id=1178002185083306616, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986586233525117, companyId=1178002185066529398, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=康美药业股份有限公司, 深圳 518000)])], figs=[ArticleFig(id=1178002187755078313, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986586233525117, language=EN, label=Fig.1, caption=Fingerprint of 19 kinds of metal elements in 65 Nelumbo nucifere Gaertn. samples, figureFileSmall=kEue2tqKnmalEw5A1NScZw==, figureFileBig=NpFCHCHksqwyn5Ef0FPc8w==, tableContent=null), ArticleFig(id=1178002187813798570, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986586233525117, language=CN, label=图1, caption=65份莲子心样品中19种金属元素的指纹图谱, figureFileSmall=kEue2tqKnmalEw5A1NScZw==, figureFileBig=NpFCHCHksqwyn5Ef0FPc8w==, tableContent=null), ArticleFig(id=1178002187868324523, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986586233525117, language=EN, label=Fig.2, caption=Fingerprint of 19 kinds of metal elements from different origins of Nelumbo nucifere Gaertn., figureFileSmall=IAOef8G7DTFsncbnFEPWcA==, figureFileBig=ce8Pg8EAXB5ev4GY9qMO6Q==, tableContent=null), ArticleFig(id=1178002187927044780, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986586233525117, language=CN, label=图2, caption=不同产地莲子心中19种金属元素的指纹图谱, figureFileSmall=IAOef8G7DTFsncbnFEPWcA==, figureFileBig=ce8Pg8EAXB5ev4GY9qMO6Q==, tableContent=null), ArticleFig(id=1178002188002542253, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986586233525117, language=EN, label=Fig.3, caption=Correlation between different metal elements and the comprehensive score of principal component analysis of Nelumbo nucifera Gaertn., figureFileSmall=dlYygOYY5yyaSDdZw19ZfQ==, figureFileBig=VgaMoKc0TtA0/4QSeoPecQ==, tableContent=null), ArticleFig(id=1178002188057068206, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986586233525117, language=CN, label=图3, caption=莲子心不同金属元素与主成分分析综合得分的相关性, figureFileSmall=dlYygOYY5yyaSDdZw19ZfQ==, figureFileBig=VgaMoKc0TtA0/4QSeoPecQ==, tableContent=null), ArticleFig(id=1178002188111594159, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986586233525117, language=EN, label=Table 1, caption=

Information of Nelumbo nucifere Gaertn. samples

, figureFileSmall=null, figureFileBig=null, tableContent=
样品编号 产地
HN-1~HN-11 湖南省湘潭市
JX-1~JX-5 江西省赣州市
JX-6~JX-16 江西省抚州市
FJ-1~FJ-8 福建省三明市
FJ-9~FJ-12 福建省武夷山市
SC-1~SC-3 四川省成都市
HB-1~HB-9 湖北省荆州市
HB-10~HB-23 湖北省宜城市
), ArticleFig(id=1178002188208063152, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986586233525117, language=CN, label=表1, caption=

莲子心样品信息

, figureFileSmall=null, figureFileBig=null, tableContent=
样品编号 产地
HN-1~HN-11 湖南省湘潭市
JX-1~JX-5 江西省赣州市
JX-6~JX-16 江西省抚州市
FJ-1~FJ-8 福建省三明市
FJ-9~FJ-12 福建省武夷山市
SC-1~SC-3 四川省成都市
HB-1~HB-9 湖北省荆州市
HB-10~HB-23 湖北省宜城市
), ArticleFig(id=1178002188266783409, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986586233525117, language=EN, label=Table 2, caption=

Information of standard solution

, figureFileSmall=null, figureFileBig=null, tableContent=
名称 来源 批号 质量浓度/(μg/mL)
标准溶液(含B、Na、Mg、Al、K、Ca、V、Cr、Mn、Fe、Co、Ni、Cu、Zn、As、Se、Sr、Cd、Ba、W) 美国SPEX公司 2-192AB 1000
混合标准溶液(含S、Mo、Pd、Re、Sb、Si、Sn、Ti、W) 美国SPEX公司 1-194AB 1000
锗标准溶液(Ge) 中国计量科学研究院国家标准物质研究中心 GSB 04-1728-2004 1000
铟标准溶液(In) 中国计量科学研究院国家标准物质研究中心 GSB 04-1731-2004 1000
铋标准溶液(Bi) 中国计量科学研究院国家标准物质研究中心 GSB 04-1719-2004 1000
铅标准溶液(Pb) 中国计量科学研究院国家标准物质研究中心 GSB 04-1742-2004 1000
砷标准溶液(As) 中国计量科学研究院国家标准物质研究中心 GSB 04-1714-2004 1000
汞标准溶液(Hg) 中国计量科学研究院国家标准物质研究中心 GSB 04-1729-2004 1000
), ArticleFig(id=1178002188342280882, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986586233525117, language=CN, label=表2, caption=

标准品溶液信息

, figureFileSmall=null, figureFileBig=null, tableContent=
名称 来源 批号 质量浓度/(μg/mL)
标准溶液(含B、Na、Mg、Al、K、Ca、V、Cr、Mn、Fe、Co、Ni、Cu、Zn、As、Se、Sr、Cd、Ba、W) 美国SPEX公司 2-192AB 1000
混合标准溶液(含S、Mo、Pd、Re、Sb、Si、Sn、Ti、W) 美国SPEX公司 1-194AB 1000
锗标准溶液(Ge) 中国计量科学研究院国家标准物质研究中心 GSB 04-1728-2004 1000
铟标准溶液(In) 中国计量科学研究院国家标准物质研究中心 GSB 04-1731-2004 1000
铋标准溶液(Bi) 中国计量科学研究院国家标准物质研究中心 GSB 04-1719-2004 1000
铅标准溶液(Pb) 中国计量科学研究院国家标准物质研究中心 GSB 04-1742-2004 1000
砷标准溶液(As) 中国计量科学研究院国家标准物质研究中心 GSB 04-1714-2004 1000
汞标准溶液(Hg) 中国计量科学研究院国家标准物质研究中心 GSB 04-1729-2004 1000
), ArticleFig(id=1178002188417778355, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986586233525117, language=EN, label=Table 3, caption=

Microwave digestion time temperature program

, figureFileSmall=null, figureFileBig=null, tableContent=
步骤 温度/℃ 保温时间/min 压力/MPa
1 130 5 1.0
2 165 10 3.0
3 180 10 4.5
), ArticleFig(id=1178002188480692916, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986586233525117, language=CN, label=表3, caption=

微波消解时间-温度程序

, figureFileSmall=null, figureFileBig=null, tableContent=
步骤 温度/℃ 保温时间/min 压力/MPa
1 130 5 1.0
2 165 10 3.0
3 180 10 4.5
), ArticleFig(id=1178002188543607477, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986586233525117, language=EN, label=Table 4, caption=

Linear equations, linear ranges, correlation coefficients, repeatability, precision, stability, spike recovery, and RSDs of 19 kinds of metal elements (n=6)

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 线性方程 线性范围
/(μg/mL)
相关系数(r) 重复性RSDs/% 中间精密度RSDs/% 稳定性
RSDs/%
平均加标
回收率/%
回收率RSDs/%
B Y=0.1133X+0.0091 0~0.50 0.9999 0.89 0.34 0.41 99.61 2.78
Na Y=3.4459X+2.3091 0~5.00 0.9997 2.34 0.16 3.35 99.36 1.17
Mg Y=1.2997X+0.0392 0~20.00 0.9999 1.95 0.25 0.93 99.51 2.29
S Y=1.6518e-4X+1.003 0~5.00 0.9993 3.05 0.35 2.55 99.11 1.34
K Y=0.3219X+0.0124 0~20.00 0.9998 1.45 0.30 0.57 99.20 0.84
Ca Y=0.0032X+1.9924e-4 0~2.00 0.9997 3.89 1.79 2.02 100.96 4.43
Mn Y=2.1235X+0.0018 0~2.00 0.9999 2.52 1.02 2.59 99.00 2.27
Fe Y=4.3291X+0.0723 0~2.00 0.9999 2.11 0.94 1.65 99.83 2.95
Ni Y=4.0008X+0.0121 0~2.00 0.9998 1.90 1.79 2.55 98.17 2.08
Zn Y=0.7991X+0.0321 0~2.00 1.0000 1.42 0.92 2.96 99.51 3.02
Sr Y=2.9238X+0.0113 0~2.00 0.9998 2.96 1.31 4.13 99.61 3.06
Mo Y=0.1082X+6.9231e-4 0~2.00 0.9999 2.39 0.98 1.26 100.18 2.21
Sb Y=0.2312X+0.0114 0~2.00 0.9999 3.29 1.69 1.68 101.71 2.40
Ba Y=0.1201X+3.2912e-4 0~2.00 0.9997 1.59 0.84 2.18 99.80 2.33
Cu Y=9.0326X+0.0019 0~2.00 0.9999 0.46 0.27 0.25 98.77 1.80
As Y=0.5893X+1.008e-3 0~0.50 0.9995 1.35 1.35 2.11 97.92 2.38
Cd Y=6.0293X+4.0932e-5 0~2.00 0.9996 1.03 1.12 0.99 99.67 3.82
Hg Y=1.2938X+2.0018e-5 0~0.01 0.9998 2.24 1.32 1.93 100.86 2.81
Pb Y=6.5773X+2.0128e-3 0~1.00 0.9998 2.21 1.47 1.76 99.44 3.44
), ArticleFig(id=1178002188631687862, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986586233525117, language=CN, label=表4, caption=

19种金属元素的线性方程、线性范围、相关系数、重复性、精密度、稳定性、加标回收率及RSDs (n=6)

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 线性方程 线性范围
/(μg/mL)
相关系数(r) 重复性RSDs/% 中间精密度RSDs/% 稳定性
RSDs/%
平均加标
回收率/%
回收率RSDs/%
B Y=0.1133X+0.0091 0~0.50 0.9999 0.89 0.34 0.41 99.61 2.78
Na Y=3.4459X+2.3091 0~5.00 0.9997 2.34 0.16 3.35 99.36 1.17
Mg Y=1.2997X+0.0392 0~20.00 0.9999 1.95 0.25 0.93 99.51 2.29
S Y=1.6518e-4X+1.003 0~5.00 0.9993 3.05 0.35 2.55 99.11 1.34
K Y=0.3219X+0.0124 0~20.00 0.9998 1.45 0.30 0.57 99.20 0.84
Ca Y=0.0032X+1.9924e-4 0~2.00 0.9997 3.89 1.79 2.02 100.96 4.43
Mn Y=2.1235X+0.0018 0~2.00 0.9999 2.52 1.02 2.59 99.00 2.27
Fe Y=4.3291X+0.0723 0~2.00 0.9999 2.11 0.94 1.65 99.83 2.95
Ni Y=4.0008X+0.0121 0~2.00 0.9998 1.90 1.79 2.55 98.17 2.08
Zn Y=0.7991X+0.0321 0~2.00 1.0000 1.42 0.92 2.96 99.51 3.02
Sr Y=2.9238X+0.0113 0~2.00 0.9998 2.96 1.31 4.13 99.61 3.06
Mo Y=0.1082X+6.9231e-4 0~2.00 0.9999 2.39 0.98 1.26 100.18 2.21
Sb Y=0.2312X+0.0114 0~2.00 0.9999 3.29 1.69 1.68 101.71 2.40
Ba Y=0.1201X+3.2912e-4 0~2.00 0.9997 1.59 0.84 2.18 99.80 2.33
Cu Y=9.0326X+0.0019 0~2.00 0.9999 0.46 0.27 0.25 98.77 1.80
As Y=0.5893X+1.008e-3 0~0.50 0.9995 1.35 1.35 2.11 97.92 2.38
Cd Y=6.0293X+4.0932e-5 0~2.00 0.9996 1.03 1.12 0.99 99.67 3.82
Hg Y=1.2938X+2.0018e-5 0~0.01 0.9998 2.24 1.32 1.93 100.86 2.81
Pb Y=6.5773X+2.0128e-3 0~1.00 0.9998 2.21 1.47 1.76 99.44 3.44
), ArticleFig(id=1178002188711379639, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986586233525117, language=EN, label=Table 5, caption=

Pearson correlation coefficients between elements

, figureFileSmall=null, figureFileBig=null, tableContent=
B Na Mg S K Ca Mn Fe Ni Zn Sr Mo Sb Ba Cu As Cd Hg Pb
B 1.000
Na 0.245* 1.000
Mg 0.394** 0.018 1.000
S 0.096 0.171 0.110 1.000
K 0.180 -0.128 0.566** -0.011 1.000
Ca -0.316* 0.037 -0.507** 0.156 -0.506** 1.000
Mn -0.733** -0.300* -0.430** 0.119 -0.264* 0.524** 1.000
Fe 0.060 -0.070 0.091 -0.072 0.135 0.012 -0.118 1.000
Ni -0.118 -0.016 -0.051 0.157 0.005 0.034 0.102 0.040 1.000
Zn -0.123 0.046 -0.169 0.040 -0.169 -0.032 0.056 -0.074 -0.222 1.000
Sr -0.037 0.068 -0.067 0.020 -0.162 -0.078 0.010 0.088 -0.389** 0.190 1.000
Mo 0.396** 0.112 -0.142 -0.050 -0.238 0.032 -0.440** 0.053 -0.083 0.138 0.164 1.000
Sb -0.047 -0.086 0.123 -0.010 0.241 -0.143 0.024 -0.122 -0.145 0.023 0.020 -0.013 1.000
Ba -0.034 -0.056 0.039 -0.102 -0.054 -0.148 -0.022 0.013 -0.120 0.076 0.006 -0.308* 0.124 1.000
Cu -0.096 0.120 -0.100 -0.061 -0.090 0.261* 0.062 0.116 -0.035 -0.234 -0.273* 0 -0.075 0.045 1.000
As 0.312* -0.040 0.290* 0.164 0.165 -0.033 -0.315* 0.279* -0.030 -0.120 0.037 0.165 -0.074 0.030 -0.093 1.000
Cd 0.161 0.088 0.210 0.068 0.274* -0.342** -0.138 0.072 0.209 0.008 -0.233 -0.148 -0.050 -0.131 -0.047 -0.028 1.000
Hg -0.131 -0.030 0.354** 0.255* 0.256* -0.101 0.184 -0.124 -0.018 0.032 0.101 -0.227 0.258* -0.052 -0.099 0.028 -0.029 1.000
Pb -0.177 0.084 -0.305* 0.179 -0.234 0.226 0.095 -0.013 0.206 0.339** -0.088 0.133 -0.078 -0.175 0.003 0.119 0.075 -0.052 1.000
), ArticleFig(id=1178002188833014456, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986586233525117, language=CN, label=表5, caption=

各元素之间的Pearson相关性系数

, figureFileSmall=null, figureFileBig=null, tableContent=
B Na Mg S K Ca Mn Fe Ni Zn Sr Mo Sb Ba Cu As Cd Hg Pb
B 1.000
Na 0.245* 1.000
Mg 0.394** 0.018 1.000
S 0.096 0.171 0.110 1.000
K 0.180 -0.128 0.566** -0.011 1.000
Ca -0.316* 0.037 -0.507** 0.156 -0.506** 1.000
Mn -0.733** -0.300* -0.430** 0.119 -0.264* 0.524** 1.000
Fe 0.060 -0.070 0.091 -0.072 0.135 0.012 -0.118 1.000
Ni -0.118 -0.016 -0.051 0.157 0.005 0.034 0.102 0.040 1.000
Zn -0.123 0.046 -0.169 0.040 -0.169 -0.032 0.056 -0.074 -0.222 1.000
Sr -0.037 0.068 -0.067 0.020 -0.162 -0.078 0.010 0.088 -0.389** 0.190 1.000
Mo 0.396** 0.112 -0.142 -0.050 -0.238 0.032 -0.440** 0.053 -0.083 0.138 0.164 1.000
Sb -0.047 -0.086 0.123 -0.010 0.241 -0.143 0.024 -0.122 -0.145 0.023 0.020 -0.013 1.000
Ba -0.034 -0.056 0.039 -0.102 -0.054 -0.148 -0.022 0.013 -0.120 0.076 0.006 -0.308* 0.124 1.000
Cu -0.096 0.120 -0.100 -0.061 -0.090 0.261* 0.062 0.116 -0.035 -0.234 -0.273* 0 -0.075 0.045 1.000
As 0.312* -0.040 0.290* 0.164 0.165 -0.033 -0.315* 0.279* -0.030 -0.120 0.037 0.165 -0.074 0.030 -0.093 1.000
Cd 0.161 0.088 0.210 0.068 0.274* -0.342** -0.138 0.072 0.209 0.008 -0.233 -0.148 -0.050 -0.131 -0.047 -0.028 1.000
Hg -0.131 -0.030 0.354** 0.255* 0.256* -0.101 0.184 -0.124 -0.018 0.032 0.101 -0.227 0.258* -0.052 -0.099 0.028 -0.029 1.000
Pb -0.177 0.084 -0.305* 0.179 -0.234 0.226 0.095 -0.013 0.206 0.339** -0.088 0.133 -0.078 -0.175 0.003 0.119 0.075 -0.052 1.000
), ArticleFig(id=1178002188916900537, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986586233525117, language=EN, label=Table 6, caption=

Eigenvalues and variance contribution rates of principal components

, figureFileSmall=null, figureFileBig=null, tableContent=
主成分
因子
初始特征值 旋转载荷平方和
总计 方差百分比/% 累积百分比/% 总计 方差百分比/% 累积百分比/%
1 3.241 17.059 17.059 2.480 13.054 13.054
2 2.261 11.902 28.961 2.420 12.735 25.789
3 1.896 9.977 38.938 1.739 9.152 34.941
4 1.663 8.754 47.692 1.608 8.466 43.406
5 1.387 7.301 54.993 1.520 7.998 51.404
6 1.275 6.712 61.705 1.465 7.710 59.114
7 1.111 5.846 67.550 1.333 7.015 66.129
8 1.010 5.318 72.868 1.280 6.739 72.868
), ArticleFig(id=1178002188984009402, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986586233525117, language=CN, label=表6, caption=

主成分的特征值及方差贡献率

, figureFileSmall=null, figureFileBig=null, tableContent=
主成分
因子
初始特征值 旋转载荷平方和
总计 方差百分比/% 累积百分比/% 总计 方差百分比/% 累积百分比/%
1 3.241 17.059 17.059 2.480 13.054 13.054
2 2.261 11.902 28.961 2.420 12.735 25.789
3 1.896 9.977 38.938 1.739 9.152 34.941
4 1.663 8.754 47.692 1.608 8.466 43.406
5 1.387 7.301 54.993 1.520 7.998 51.404
6 1.275 6.712 61.705 1.465 7.710 59.114
7 1.111 5.846 67.550 1.333 7.015 66.129
8 1.010 5.318 72.868 1.280 6.739 72.868
), ArticleFig(id=1178002189059506875, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986586233525117, language=EN, label=Table 7, caption=

Component matrix after rotation transformation

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 主成分因子
1 2 3 4 5 6 7 8
B 0.230 0.815 -0.028 -0.131 0.048 0.134 -0.036 -0.066
Na -0.147 0.545 0.026 0.047 0.396 -0.341 -0.294 0.174
Mg 0.617 0.271 0.000 -0.334 0.305 0.211 0.201 0.103
S -0.056 0.021 0.051 0.126 0.816 0.065 -0.070 -0.086
K 0.683 0.025 0.165 -0.264 0.068 0.193 0.313 -0.007
Ca -0.808 -0.271 0.094 0.011 0.163 0.054 -0.087 -0.120
Mn -0.326 -0.854 0.009 0.027 0.138 -0.157 -0.009 -0.019
Fe 0.033 -0.013 0.002 -0.064 -0.140 0.719 -0.226 0.076
Ni 0.115 -0.203 0.602 0.054 0.115 0.045 -0.265 -0.279
Zn 0.051 -0.017 -0.288 0.788 -0.014 -0.138 0.051 0.142
Sr -0.030 -0.009 -0.859 0.061 0.072 0.043 -0.108 -0.048
Mo -0.284 0.613 -0.160 0.213 -0.229 0.103 0.111 -0.478
Sb 0.110 -0.019 -0.007 0.050 0.012 -0.140 0.821 0.073
Ba 0.031 -0.054 -0.076 0.040 -0.109 0.075 0.071 0.875
Cu -0.490 0.117 0.454 -0.304 -0.039 0.005 0.067 0.281
As 0.036 0.275 -0.031 0.043 0.230 0.780 0.071 -0.013
Cd 0.582 0.070 0.409 0.162 0.044 -0.103 -0.295 -0.036
Hg 0.235 -0.253 -0.151 -0.108 0.606 -0.052 0.413 -0.054
Pb -0.220 -0.035 0.294 0.760 0.157 0.137 -0.016 -0.153
), ArticleFig(id=1178002189151781564, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986586233525117, language=CN, label=表7, caption=

旋转变换后的成分矩阵

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 主成分因子
1 2 3 4 5 6 7 8
B 0.230 0.815 -0.028 -0.131 0.048 0.134 -0.036 -0.066
Na -0.147 0.545 0.026 0.047 0.396 -0.341 -0.294 0.174
Mg 0.617 0.271 0.000 -0.334 0.305 0.211 0.201 0.103
S -0.056 0.021 0.051 0.126 0.816 0.065 -0.070 -0.086
K 0.683 0.025 0.165 -0.264 0.068 0.193 0.313 -0.007
Ca -0.808 -0.271 0.094 0.011 0.163 0.054 -0.087 -0.120
Mn -0.326 -0.854 0.009 0.027 0.138 -0.157 -0.009 -0.019
Fe 0.033 -0.013 0.002 -0.064 -0.140 0.719 -0.226 0.076
Ni 0.115 -0.203 0.602 0.054 0.115 0.045 -0.265 -0.279
Zn 0.051 -0.017 -0.288 0.788 -0.014 -0.138 0.051 0.142
Sr -0.030 -0.009 -0.859 0.061 0.072 0.043 -0.108 -0.048
Mo -0.284 0.613 -0.160 0.213 -0.229 0.103 0.111 -0.478
Sb 0.110 -0.019 -0.007 0.050 0.012 -0.140 0.821 0.073
Ba 0.031 -0.054 -0.076 0.040 -0.109 0.075 0.071 0.875
Cu -0.490 0.117 0.454 -0.304 -0.039 0.005 0.067 0.281
As 0.036 0.275 -0.031 0.043 0.230 0.780 0.071 -0.013
Cd 0.582 0.070 0.409 0.162 0.044 -0.103 -0.295 -0.036
Hg 0.235 -0.253 -0.151 -0.108 0.606 -0.052 0.413 -0.054
Pb -0.220 -0.035 0.294 0.760 0.157 0.137 -0.016 -0.153
), ArticleFig(id=1178002189223084733, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986586233525117, language=EN, label=Table 8, caption=

Score coefficient matrix of components after rotation transformation

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 主成分因子
1 2 3 4 5 6 7 8
B 0.013 0.331 -0.001 -0.062 0.044 -0.003 -0.019 -0.025
Na -0.099 0.303 0.010 -0.011 0.321 -0.297 -0.227 0.212
Mg 0.177 0.064 -0.010 -0.141 0.182 0.083 0.065 0.056
S -0.057 0.028 0.001 0.048 0.549 0.039 -0.072 0.002
K 0.239 -0.051 0.097 -0.075 -0.010 0.097 0.179 -0.057
Ca -0.351 -0.050 0.047 -0.080 0.142 0.095 0.024 -0.058
Mn -0.063 -0.341 -0.033 -0.038 0.088 -0.018 -0.026 -0.041
Fe 0.010 -0.092 -0.028 -0.004 -0.087 0.513 -0.173 0.079
Ni 0.096 -0.105 0.304 0.038 0.040 0.029 -0.157 -0.190
Zn 0.097 0.007 -0.106 0.529 -0.021 -0.047 0.051 0.169
Sr 0.030 -0.056 -0.537 -0.038 0.080 0.034 -0.193 -0.063
Mo -0.158 0.270 -0.041 0.094 -0.158 0.035 0.201 -0.350
Sb -0.042 0.048 0.105 0.107 -0.039 -0.075 0.665 0.015
Ba -0.018 0.011 0.008 0.123 -0.028 0.091 0.011 0.707
Cu -0.302 0.140 0.300 -0.179 0.012 0.008 0.148 0.244
As -0.065 0.058 -0.004 0.078 0.146 0.538 0.082 0.040
Cd 0.308 -0.012 0.204 0.156 -0.006 -0.111 -0.253 -0.002
Hg 0.050 -0.105 -0.091 -0.063 0.374 -0.028 0.239 -0.071
Pb -0.051 0.015 0.225 0.506 0.073 0.150 0.115 -0.016
), ArticleFig(id=1178002189294387902, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986586233525117, language=CN, label=表8, caption=

旋转变换后的成分得分系数矩阵

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 主成分因子
1 2 3 4 5 6 7 8
B 0.013 0.331 -0.001 -0.062 0.044 -0.003 -0.019 -0.025
Na -0.099 0.303 0.010 -0.011 0.321 -0.297 -0.227 0.212
Mg 0.177 0.064 -0.010 -0.141 0.182 0.083 0.065 0.056
S -0.057 0.028 0.001 0.048 0.549 0.039 -0.072 0.002
K 0.239 -0.051 0.097 -0.075 -0.010 0.097 0.179 -0.057
Ca -0.351 -0.050 0.047 -0.080 0.142 0.095 0.024 -0.058
Mn -0.063 -0.341 -0.033 -0.038 0.088 -0.018 -0.026 -0.041
Fe 0.010 -0.092 -0.028 -0.004 -0.087 0.513 -0.173 0.079
Ni 0.096 -0.105 0.304 0.038 0.040 0.029 -0.157 -0.190
Zn 0.097 0.007 -0.106 0.529 -0.021 -0.047 0.051 0.169
Sr 0.030 -0.056 -0.537 -0.038 0.080 0.034 -0.193 -0.063
Mo -0.158 0.270 -0.041 0.094 -0.158 0.035 0.201 -0.350
Sb -0.042 0.048 0.105 0.107 -0.039 -0.075 0.665 0.015
Ba -0.018 0.011 0.008 0.123 -0.028 0.091 0.011 0.707
Cu -0.302 0.140 0.300 -0.179 0.012 0.008 0.148 0.244
As -0.065 0.058 -0.004 0.078 0.146 0.538 0.082 0.040
Cd 0.308 -0.012 0.204 0.156 -0.006 -0.111 -0.253 -0.002
Hg 0.050 -0.105 -0.091 -0.063 0.374 -0.028 0.239 -0.071
Pb -0.051 0.015 0.225 0.506 0.073 0.150 0.115 -0.016
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电感耦合等离子体质谱法测定不同产地莲子心中19种金属元素及其主成分分析
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赖志坚 # , 陈秋玲 #, * , 刘国伟 , 张津津 , 黄勇 , 石诚 , 杨晓彬 , 姚艺新
食品安全质量检测学报 | 本期专题:现代分析仪器在食品检测中的应用 2025,16(4): 185-193
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食品安全质量检测学报 | 本期专题:现代分析仪器在食品检测中的应用 2025, 16(4): 185-193
电感耦合等离子体质谱法测定不同产地莲子心中19种金属元素及其主成分分析
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赖志坚# , 陈秋玲#, * , 刘国伟, 张津津, 黄勇, 石诚, 杨晓彬, 姚艺新
作者信息
  • 康美药业股份有限公司, 深圳 518000
  • 赖志坚(1969—), 男, 硕士, 高级工程师, 主要研究方向为中药质量标准研究。E-mail:

通讯作者:

* 陈秋玲(1989—), 女, 硕士, 执业中药师, 主要研究方向为食品药品质量标准研究。E-mail:
Determination and principal component analysis on 19 kinds of metal elements in Nelumbo nucifere Gaertn. from different origins by inductively coupled plasma-mass spectrometry
Zhi-Jian LAI , Qiu-Ling CHEN* , Guo-Wei LIU, Jin-Jin ZHANG, Yong HUANG, Cheng SHI, Xiao-Bin YANG, Yi-Xin YAO
Affiliations
  • Kangmei Pharmaceutical Co., Ltd., Shenzhen 518000, China
出版时间: 2025-02-25 doi: 10.19812/j.cnki.jfsq11-5956/ts.20241029003
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目的 建立莲子心19种金属元素的电感耦合等离子体质谱法(inductively coupled plasma-mass spectrometry, ICP-MS)的分析方法, 并对不同产地莲子心金属元素含量进行比较分析。方法 莲子心样品经微波消解, 采用ICP-MS测定金属元素含量, 并绘制金属元素指纹图谱, 采用SPSS 26.0对金属元素含量进行主成分分析。结果 莲子心19种金属元素指纹图谱具有一定的特征性; 有害金属元素含量应引起关注。主成分分析筛选出8个主因子, 得出B、S、Ca、Mn、Fe、Zn、Sr、Sb、Ba、As、Pb是莲子心的特征金属元素; 与主成分分析结果呈正相关的元素相关性从大到小依次为Pb、As、Ba、Zn、Sb、Mg、Cd、K、S、B、Na、Hg、Cu、Fe、Ni; 呈负相关的元素相关性从大到小依次为Sr、Mn、Ca、Mo。结论 该方法快速、准确、灵敏度高, 适用于测定莲子心多种金属元素含量的同时测定, 为莲子心的质量控制及安全性评价提供依据。

莲子心  /  金属元素  /  主成分分析  /  电感耦合等离子体质谱法

Objective To establish a method for the analysis of 19 kinds of metal elements in Nelumbo nucifere Gaertn. by inductively coupled plasma-mass spectrometry (ICP-MS), and to compare and analyze the metal elements content from different areas. Methods The Nelumbo nucifere Gaertn. sample was digested by microwave, and the metal elements content was determined by ICP-MS. The metal element fingerprint was drawn, and principal component analysis was performed on the metal element content using SPSS 26.0 software. Results The fingerprint of 19 kinds of metal elements in the Nelumbo nucifere Gaertn. had certain characteristics, and the content of harmful metal elements should be of concerned. Principal component analysis identified 8 main factors and identified B, S, Ca, Mn, Fe, Zn, Sr, Sb, Ba, As, and Pb as characteristic metal elements for Nelumbo nucifere Gaertn.. The correlation of 19 kinds of metal elements with the comprehensive score value of principal component analysis that were positively correlated in decreasing order were as follows: Pb, As, Ba, Zn, Sb, Mg, Cd, K, S, B, Na, Hg, Cu, Fe, Ni, and negatively correlated correlated in decreasing order were as follows: Sr, Mn, Ca, Mo. Conclusion The method is rapid, accurate and sensitive, and can be used for the simultaneous determination of the content of various metal elements in Nelumbo nucifere Gaertn.. It provides the basis for the quality control and safety evaluation of Nelumbo nucifere Gaertn..

Nelumbo nucifere Gaertn.  /  metal elements  /  principal component analysis  /  inductively coupled plasma-mass spectrometry
赖志坚, 陈秋玲, 刘国伟, 张津津, 黄勇, 石诚, 杨晓彬, 姚艺新. 电感耦合等离子体质谱法测定不同产地莲子心中19种金属元素及其主成分分析. 食品安全质量检测学报, 2025 , 16 (4) : 185 -193 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20241029003
Zhi-Jian LAI, Qiu-Ling CHEN, Guo-Wei LIU, Jin-Jin ZHANG, Yong HUANG, Cheng SHI, Xiao-Bin YANG, Yi-Xin YAO. Determination and principal component analysis on 19 kinds of metal elements in Nelumbo nucifere Gaertn. from different origins by inductively coupled plasma-mass spectrometry[J]. Journal of Food Safety & Quality, 2025 , 16 (4) : 185 -193 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20241029003
药食同源物质是指既是食品又是中药材的物质, 莲子是首批被列入我国卫生部公布的药食同源名单的品种之一。莲子属于睡莲科植物莲的种子, 既可以作为食物食用, 也可以作为中药使用。莲子心来源于莲科植物莲(Nelumbo nucifera Gaertn.)的成熟种子中的干燥幼叶及胚根, 具有“清心安神、交通心肾、涩精止血”功效。
近年来研究表明金属元素通过调节植物的生长而影响有效成分的积累。金属元素是维持人体正常新陈代谢和生命活动的重要物质, 与人体健康密不可分, 可分为常量元素和必需微量元素, 适宜的金属元素含量能使人体的健康保持在最佳状态, 缺乏和过量都与人们的健康息息相关[1-5]。缺乏相关元素可能会引起人体器官功能失调或病理变化。对于人体健康的影响非常复杂, 元素进入人体后, 部分会与生物大分子结合, 以多种金属酶、金属激素、氨基酸和蛋白质的金属络合物等形式调节人体新陈代谢。部分高浓度微量元素可能对人体有害, 而必须微量元素的过度消耗, 则可能会导致由酶功能障碍引起的人体代谢平衡失调[6-11]。S是人体内蛋白质的重要组成元素, K、Mg、Na和Ca是人体必需的常量元素, Mg影响细胞的多种生物功能, 影响K+和Ca2+的转运, 调控信号的传递, 参与能量代谢、蛋白质和核酸的合成[12-17]; Fe参与血红蛋白、肌红蛋白及多种含铁酶的合成, 参与物质代谢过程; Zn元素是免疫器官胸腺发育的营养素; Cd对儿童的成长具有明显的毒害作用; Mn能激活人体内的多种酶, 有抗衰老、抗突变的作用, 抑制肿瘤的发生、发展[18-21]; Mo是黄嘌呤氧化酶、醛氧化酶和亚硫酸氧化酶的组成成份; Ni是核酸、镍胞浆素的组成成份; Sr具有抗衰、防老、抗癌、促进骨修复作用, 与骨骼的形成密切相关, 为人体骨骼及牙齿的组成部分[22-26]。重金属及有害元素是安全性评价的重要指标, 有害金属元素Pb、Hg、Cu、Cd、As危害人体健康, 对产品质量同样有重要的影响。重金属被摄入人体后会在体内累积, 当达到一定水平时, 可对人体器官组织造成危害。2020年版中国药典四部9302《中药有害残留物限量制定指导原则》制定了药材及饮片(植物类)重金属及Pb、Hg、As、Cd、Cu有害金属元素的限量标准[27-29]。因此, 加强对中药材及其饮片的重金属及有害元素的监测具有重要意义。
目前金属元素的测定方法主要有电感耦合等离子体质谱(inductively coupled plasma-mass spectrometry, ICP-MS)法、电感耦合等离子体发射光谱(inductively coupled plasma-atomic emission spectrometry, ICP-AES)法以及原子吸收光谱(atomic absorption spectrometry, AAS)法。其中AAS法存在耗时长、检出限较高、基体效应大、线性范围窄、且难以实现多元素同时分析的问题。ICP-AES法虽可以同时测定多种元素, 但存在谱线干扰多, 灵敏度较低。ICP-MS法具有分析速度快、检出限低、基体效应小、精密度高、灵敏度高、线性范围宽及多元素同时分析等优点。微波消解法利用微波快速加热, 在高压环境下进行消解, 具有消解速度快、污染小、样品消解完全、回收率高、用酸少、安全、污染程度低等优点[30-34]
指纹图谱是近年来用于表征天然植物中多成分特征的一种综合性质量分析方法, 可以较为全面地反映出天然植物多成分体系的整体状况, 一般指纹图谱常用于天然植物内有机活性成分的分析。当前对莲子心的无机元素进行指纹图谱分析研究的报道相对较少。本研究运用ICP-MS法分析莲子心的金属元素, 以4大产区(湖南、江西、福建、湖北)收集的65份莲子心样品为研究对象, 分析测定其19种金属元素含量, 结合主成分分析法(principal component analysis, PCA)探讨不同产地莲子心中金属元素之间的差异, 以期为莲子心全面、客观、科学地进行品质评价提供参考依据。
莲子心的样品分别从湖南省湘潭市、江西省赣州市和抚州市、福建省三明市和武夷山市、湖北省荆州市和宜城市共收集65份, 样品具体信息详见表1, 由康美药业股份有限公司质量管理部刘茂贵主任药师根据其性状特征分别鉴定为睡莲科植物莲的成熟种子中的干燥幼叶及胚根。浓硝酸(电子纯, 天津市科密欧化学试剂有限公司)。标准品溶液具体信息详见表2
CEM MARS6型微波消解仪(德国Berghof公司); 7900型电感耦合等离子体质谱仪(美国安捷伦公司); BSA 224S型万分之一电子分析天平(德国赛多利斯公司); Milli-Q型超纯水机(美国Millipore Bedford MA公司)。
多元素混合对照品溶液1的制备: 取多元素混合标准溶液(含S、Mo、Pd、Re、Sb、Si、Sn、Ti、W)用10%硝酸配制成质量浓度分别为1、5、10、50、100、500、1000、5000 ng/mL混合对照品溶液。
多元素混合对照品溶液2的制备: 取多元素混合标准溶液(含B、Na、Mg、K、Ca、Mn、Fe、Co、Ni、Cu、Zn、As、Se、Sr、Cd、Ba)用10%硝酸配制成质量浓度分别为1、5、10、50、100、500、1000、5000、20000 ng/mL的混合对照品溶液。
多元素混合对照品溶液3的制备: 分别取As、Pb标准溶液0.5 mL用10%硝酸定容至50 mL, 配制成多元素混合对照品标准溶液(含As、Pb)母液, 再用10%硝酸稀释母液配制成质量浓度分别为0.5、1.0、5.0、10.0、50.0、100.0 ng/mL的对照品溶液。
Hg单元素对照品溶液的制备: 取Hg单元素标准溶液0.1 mL, 用10%硝酸溶液定容至100 mL, 配制成Hg元素标准溶液母液, 质量浓度为1 μg/mL。再用10%硝酸稀释Hg元素母液配制成质量浓度分别为0.1、0.5、1.0、5.0、10.0 ng/mL的对照品溶液。
分别吸取Ge、In、Bi标准溶液0.5 mL用10%硝酸定容至50 mL, 即为质量浓度为10 μg/mL的混合内标溶液。
以灵敏度、背景、稳定性等各项指标对仪器的工作参数进行优化。测定条件: 等离子射频功率1550 W, 等离子气体15 L/min, 辅助气体流量1 L/min, 雾化气流量1 L/min, 补偿/稀释气体1 L/min, 雾化室温度2 ℃, 蠕动泵速度0.1 r/s。重复次数3次; 数据采样模式: 质谱图; 采样锥/截取锥为镍锥; 检测器模式为P/A; 采样深度为10 mm; 以72Ge、115In、209Bi为内标元素, 监测信号的变动情况, 能有效克服仪器信号的漂移和校正基体效应。
取莲子心样品粉末0.2 g(过40目筛), 精密称定, 于聚四氟乙烯消解罐中, 置于通风橱, 加入浓硝酸8 mL, 浸泡过夜。第2 d放入微波消解仪中, 按设定的消解程序(见表3)进行消解。消解完毕后, 冷却至室温, 取出消解罐, 在通风橱中将酸挥尽, 转移用去离子水定容至50 mL。
除不加莲子心样品粉末外, 其余制备方法与供试品溶液的制备方法相同, 制成空白对照溶液。
采用Microsoft Excel 2019进行数据计算和统计, 采用IBM SPSS Statistics 26.0对实验数据进行统计分析, 进行元素间相关性分析、主成分分析。
使用1.3.1配制好的各系列标准品工作溶液和1.3.2配制好的内标工作溶液, 分别以各元素质量浓度为横坐标(X, μg/mL), 以样品溶液与内标工作溶液响应值的比值为纵坐标(Y), 分别绘制标准曲线, 得到各元素回归方程、相关系数和线性范围见表4。结果表明19种金属元素在各自的线性范围内线性关系良好r≥0.99, 可满足方法学要求。
精密称取0.2 g莲子心样品粉末, 制备供试品溶液, 平行制备6份, 测定19种元素的量。各元素的重复性RSDs在0.46%~3.89%, 表明方法的重复性良好。不同时间不同试验人员重新制备6份供试品溶液, 测定19种元素的量, 计算12份数据(包括重复性)的RSD, 作为中间精密度结果。中间精密度RSDs在0.16%~1.79%, 表明本方法中间精密度良好。
精密称取0.2 g莲子心样品粉末, 制备供试品溶液, 溶液在2~8 ℃的条件下保存, 分别于制样后0、2、6、8、12、24 h进样, 测定19种元素的含量。各元素的稳定性RSDs在0.25%~4.13%之间, 表明供试品溶液在24 h内稳定性良好(见表4)。
精密称取0.2 g莲子心样品粉末6份, 分别加入与样品中所测定元素含量相当的对照品, 分别加入一定量的各元素标准溶液, 制备加样供试品溶液, 分别进行测定, 计算得到各元素的平均回收率在97.92%~101.71%之间, 回收率RSDs在0.84%~4.43%之间。结果表明回收率良好。
莲子心样品种19种金属元素含量存在一定的差异, 其中元素Mg、S、K的含量较高, 达到g/kg数量级; 其次含量较高的元素为B、Na、Ca、Mn、Fe、Cu、Zn, 而Ni、Sr、Mo、Sb、Ba、As、Cd、Hg、Pb的含量较低。从测定结果可以看出, 所收集的莲子心样品中, 大多数金属元素的量均有明显差异, 同一元素在不同产地之间的含量存在较大差异, 如Mg元素含量最高值为1833.23 mg/kg, 最低值为209.38 mg/kg, K元素含量最高值为1402.98 mg/kg, 最低值为923.19 mg/kg。就有害金属元素而言, 所有平均含量由高到低依次为Cu、Pb、Cd、As、Hg。在测定的65种莲子心样品中, Cu在1.92~13.26 mg/kg, 均值4.33 mg/kg; Cd在0.02~0.17 mg/kg, 均值为0.11 mg/kg; Pb在0.00~1.27 mg/kg, 均值为0.14 mg/kg; As在0.00~ 0.25 mg/kg, 均值为0.06 mg/kg; Hg在0.00~0.22 mg/kg, 均值为0.03 mg/kg。2020年版中国药典已经制定了重金属及有害元素一致性限量指导值Pb不得过5 mg/kg, Cd不得过1 mg/kg, As不得过2 mg/kg, Hg不得过0.2 mg/kg, Cu不得过20 mg/kg。65份样品中有2份Hg元素超标, 超标率为3%。
由于莲子心样品中19种金属元素含量差别较大, 通过金属元素指纹图谱可以比较直观的感受各地区之间金属元素的含量差异。为了使金属元素指纹图谱更加直观, 便于绘制, 将不同元素的含量扩大或缩小至统一数量级(Mg、S、K缩小100倍, Fe、Sr、Mo、Ba、Pb扩大10倍, Ni、Sb、As、Cd、Hg扩大10倍), 以元素种类为横坐标(X), 相对含量为纵坐标(Y), 绘制指纹图谱见图1。取不同产地莲子心样品金属元素含量的平均值绘制指纹图谱见图2
为进一步分析莲子心中各元素之间的相关性。运用SPSS 26.0计算19种元素的皮尔逊(Pearson)相关系数(表5)。结果表明不同地区莲子心中金属元素之间存在一定的相互作用关系。B-Mg、B-Mo、Mg-K、Mg-Hg和Ca-Mn元素间达到极显著正相关(P<0.01)。B-Na、B-As、Mg-As、S-Hg、K-Cd、K-Hg、Ca-Cu、Fe-As和Sb-Hg元素间达到显著正相关(P<0.05)。B-Mn、Mg-Ca、Mg-Mn、K-Ca、Ca-Cd、Mn-Mo和Ni-Sr元素间达到极显著负相关(P<0.01)。B-Ca、Na-Mn、Mg-Pb、K-Mn、Mn-As、Sr-Cu和Mo-Ba元素间达到显著负相关(P<0.05)。
主成分分析是利用降维的方式将原始多个变量拟合为少数的几个主成分, 且尽可能多地保留原始变量的信息, 为进一步探索不同产地莲子心金属元素间的关系, 运用SPSS 26.0进行主成分分析。主成分的特征值(大于1)及方差贡献率是选择主成分的依据, 结果提取到8个主成分因子。主成分因子的特征值和方差贡献率见表6
为进一步确定造成质量差异的主要金属元素, 通过成分矩阵筛选出特征元素见表7表7是经方差最大正交旋转后的成分矩阵。其中可以看出第1个主因子和Ca呈高度负相关; 第2个主因子和B呈高度正相关, 和Mn呈高度负相关; 第3个主因子和Sr呈高度负相关; 第4个主因子和Zn、Pb呈高度正相关; 第5个主因子和S呈高度正相关; 第6个主因子和Fe、As高度正相关; 第7个主因子和Sb呈高度正相关; 第8个主因子和Ba呈高度正相关; 所以可以认为B、S、Ca、Mn、Fe、Zn、Sr、Sb、Ba、As、Pb是莲子心的特征金属元素。旋转变换后的成分得分系数矩阵见表8
计算8个主成分因子的表达式, 主成分因子分别用Y1Y2Y3Y4Y5Y6Y7Y8, 表达式如下:
Y1=0.013×B-0.099×Na+0.177×Mg-0.057×S+0.239×K-0.351×Ca-0.063×Mn+0.010×Fe+0.096×Ni+0.097×Zn+0.030×Sr-0.158×Mo-0.042×Sb-0.018×Ba-0.302×Cu-0.065×As+0.308×Cd+0.05×Hg-0.051×Pb
Y2=0.331×B+0.303×Na+0.064×Mg+0.028×S-0.051×K-0.050×Ca-0.341×Mn-0.092×Fe-0.105×Ni+0.007×Zn-0.056×Sr+0.270×Mo+0.048×Sb+0.011×Ba+0.140×Cu+0.058×As-0.012×Cd-0.105×Hg+0.015×Pb
Y3=-0.001×B+0.010×Na-0.010×Mg+0.001×S+0.097×K+0.047×Ca-0.033×Mn-0.028×Fe+0.304×Ni-0.106×Zn-0.537×Sr-0.041×Mo+0.105×Sb+0.008×Ba+0.300×Cu-0.004×As+0.204×Cd-0.091×Hg+0.225×Pb
Y4=-0.062×B-0.011×Na-0.141×Mg+0.048×S-0.075×K-0.080×Ca-0.038×Mn-0.004×Fe+0.038×Ni+0.529×Zn-0.038×Sr+0.094×Mo+0.107×Sb+0.123×Ba-0.179×Cu+0.078×As+0.156×Cd-0.063×Hg+0.506×Pb
Y5=0.044×B+0.321×Na+0.182×Mg+0.549×S-0.010×K+0.142×Ca+0.088×Mn-0.087×Fe+0.040×Ni-0.021×Zn+0.080×Sr-0.158×Mo-0.039×Sb-0.028×Ba+0.012×Cu+0.146×As-0.006×Cd+0.374×Hg+0.073×Pb
Y6=-0.003×B-0.297×Na+0.083×Mg+0.039×S+0.097×K+0.095×Ca-0.018×Mn+0.513×Fe+0.029×Ni-0.047×Zn+0.034×Sr+0.035×Mo-0.075×Sb+0.091×Ba+0.008×Cu+0.538×As- 0.111×Cd-0.028×Hg+0.150×Pb
Y7=-0.019×B-0.227×Na+0.065×Mg-0.072×S+0.179×K+0.024×Ca-0.026×Mn-0.173×Fe-0.157×Ni+0.051×Zn-0.193×Sr+0.201×Mo+0.665×Sb+0.011×Ba+0.148×Cu+0.082×As-0.253×Cd+0.239×Hg+0.115×Pb
Y8=-0.025×B+0.212×Na+0.056×Mg+0.002×S-0.057×K-0.058×Ca-0.041×Mn+0.079×Fe-0.190×Ni+0.169×Zn-0.063×Sr-0.350×Mo+0.015×Sb+0.707×Ba+0.244×Cu+0.040×As-0.002×Cd-0.071×Hg-0.016×Pb
结合表6主成分因子的特征值和方差贡献率的数据。得到主成分因子总值Y表达式如下:
Y=Y1×13.054/72.868+Y2×12.735/72.868+Y3×9.152/72.868+ Y4×8.466/72.868+Y5×7.998/72.868+Y6×7.710/72.868+Y7×7.015/72.868+Y8×6.739/72.868=0.053×B+0.037×Na+0.065×Mg+0.058×S+0.058×K-0.052×Ca-0.078×Mn+0.017×Fe+0.016×Ni+0.080×Zn-0.088×Sr-0.002×Mo+0.080×Sb+0.087×Ba+0.026×Cu+0.092×As+0.060×Cd+0.026×Hg+0.114×Pb
Y表达式中以每种元素的系数来代表金属元素与主成分分析分析综合得分的相关性, 见图3。根据Y表达式, 与主成分分析的结果呈正相关的元素的相关性从大到小依次为Pb、As、Ba、Zn、Sb、Mg、Cd、K、S、B、Na、Hg、Cu、Fe、Ni; 呈负相关的元素的相关性从大到小依次为Sr、Mn、Ca、Mo。
基体效应主要来源于样品基体或酸溶剂中的元素和等离子体用的氩气中的杂质。由于基体效应会对待测元素产生一定的干扰作用。本研究通过在线加入内标Ge、In、Bi元素的方法来校正基体效应和干扰。其中B、Na、Mg、S、K、Ca、Mn、Fe、Ni、Cu、Zn、As以Ge作为内标准溶液, Sr、Mo、Sb、Ba、Cd以In作为内标准溶液, Hg、Pb以Bi作为内标准溶液。内标元素回收率在80%~120%之间, 能有效地校正分析信号的漂移。
近年来, 金属元素已作为食品的质量评估和安全性评价的指标之一, 其中食用植物生长所需的土壤、气候、水文等生态因子对矿物元素的积累有着至关重要的作用。本研究建立了ICP-MS测定莲子心19种金属元素含量的方法, 本方法准确性高, 灵敏度好。本研究采用ICP-MS分析65批不同产地莲子心样品中19种金属元素, 所收集的莲子心样品中, 大多数金属元素的量均有明显差异, 同一元素在不同产地之间的含量存在较大差异。其中元素Mg、S、K的含量较高, 达到g/kg数量级; 运用SPSS 26.0计算19种元素的Pearson相关系数结果表明不同地区莲子心中金属元素之间存在一定的相互作用关系。进一步对不同产地莲子心金属元素含量进行主成分分析。主成分的特征值(大于1)及方差贡献率是选择主成分的依据, 结果提取到8个主成分因子。通过主成分分析和特征元素分析发现不同地区生长的莲子心金属元素含量的差异较大, B、S、Ca、Mn、Fe、Zn、Sr、Sb、Ba、As和Pb这11种特征元素可能是湖南省湘潭市、江西省赣州市、江西省抚州市、福建省三明市、福建省武夷山市、四川省成都市、湖北省荆州市、湖北省宜城市等地区莲子心中金属元素关键的差异标志物。通过对不同产地的莲子心金属元素分析比较能为莲子心的质量控制及安全性评价提供依据, 为莲子心产地溯源模型的建立提供数据支持。
  • 国家中药标准化项目(ZYBZH-Y-GD-13)
  • 中药配方颗粒产品研发项目(KMYY20220801)
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2025年第16卷第4期
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doi: 10.19812/j.cnki.jfsq11-5956/ts.20241029003
  • 接收时间:2024-10-29
  • 首发时间:2025-07-21
  • 出版时间:2025-02-25
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  • 收稿日期:2024-10-29
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国家中药标准化项目(ZYBZH-Y-GD-13)
中药配方颗粒产品研发项目(KMYY20220801)
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    康美药业股份有限公司, 深圳 518000

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* 陈秋玲(1989—), 女, 硕士, 执业中药师, 主要研究方向为食品药品质量标准研究。E-mail:
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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